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Reliable secular time series of essential climatic variables are a fundamental element for the assessment of vulnerability, impact and adaptation to climate change. Here, we implement a readily portable procedure for building an upgradable long‐term homogeneous climate dataset using monthly and daily observations of temperature and precipitation over a given area of interest, exemplified here with Abruzzo, a region in Central Italy characterized by complex orography. We process the dataset according to a preliminary ranking of stations based on data quantity and quality, and we exploit the Climatol algorithm for inhomogeneity correction. The corrected time series show trends in broad agreement with external databases (CRU, Berkeley Earth, E‐OBS), and highlight the importance of relying on a local network for a better representation of gradients and variability over the territory. We estimate that maximum (TX) and minimum temperature (TN) increased by ~1.6 and ~2.2°C/century, respectively, over the period 1930–2019, while in the recent decades 1980–2019 we found an accelerated trend of ~5.7 and ~3.9°C/century. Precipitation (RR) decreased by ~10%/century in 1930–2019, while it has been increasing at a rate of ~26%/century in 1980–2019. The Köppen–Geiger climate classification is sensitive to the increase of precipitation in the recent decades, which is attributable to decreased summer precipitation overcompensated by more rain in late spring and early autumn. The cold climate types are retreating upwards along the slopes of the mountain ranges. Over the period 1980–2019, extreme values are also displaying significant trends. Every 2 years, there is one less frost day (TN 25°C) in the Apennines area, while there is one more tropical night (TN >20°C) in the Adriatic coastal area. Precipitation extremes are increasing, especially along the coast, with rain accumulated in the rainiest days increasing at a rate of 1–2%/year.

Large-scale gridded climatic data can be useful for the assessment of climate variability and change as a basis for understanding and monitoring natural hazards, as well as for determining appropriate coping strategies. However, an evaluation of the accuracy of these data products against local observational measurements over the different regions of the globe is always required, as these large-scale data may be affected by systematic errors, which can affect the results of downstream applications. Therefore, this study was carried out to evaluate the performances of two long-term gridded datasets in reproducing station-based precipitation and temperature data over the Apulia region (southern Italy) for the period 1956–2019, with a particular focus on the effect of using the different data sources on the results of trend analyses and aridity classification. The results revealed that the considered gridded data products allow only general indications on the spatial and temporal behavior of climatic variables over the Apulia region, especially in regard to precipitation data.

This study presents an investigation on the use of submerged counterflow jets as a means for stabilizing the spatial hydraulic jump occurring in abruptly expanding channels. The characteristics of the flow downstream from the stilling basin and the main parameters influencing the effectiveness of the device in improving flow uniformity and reducing scouring potential are examined in laboratory tests, under several geometric configurations and hydraulic boundary conditions. The position within the stilling basin and the jet density (i.e., the number of orifices issuing the counterflow jets) were found to be important parameters influencing the performance of the device. Overall, the results indicate that this dissipation system has promising capabilities in forcing the transition from supercritical to subcritical flow, by significantly shortening the protection length needed to limit the phenomena of instability associated with spatial hydraulic jumps.

Side weirs are particular structures used in hydraulic engineering for flow control in rivers and channels. In movable bed situations, the lateral discharge withdrawal can influence sediment transport processes causing an unexpected functioning of the weir; due to the possible changes in bed morphology, sediments from the main channel can be diverted in the evacuation channel as well. This paper summarizes the results of experimental analyses carried out to study these interactions for inclined weirs, under different hydraulic and geometric conditions. The results show the influence of weir’s length and inclination of the crest on the pattern of deposition and erosion zones in the main channel. The analysis of the experimental observations also confirm the validity of the De Marchi’s approach for modelling the behavior of inclined side weirs on movable beds. In addition, the predictive capability of a numerical method for estimating the diverted solid discharge from side weirs is tested. The comparison of observed and predicted sediment discharges outflowing from the lateral structure indicates the reliability of the tested method also for inclined side weirs.

The development of reliable models for different exposed sectors is key for obtaining more comprehensive flood damage and risk assessments. This study discusses the implementation of the recent conceptual damage model for crops, AGRIDE-c, to a central region of Italy, in order to demonstrate its potential for application and related challenges from a flood risk assessment perspective at the river basin scale. The process for adaptation of model's components to the local characteristics of the investigated area is first described, including the extension of the analytical flood loss model to annual vegetables and perennial crops (here exemplified for grapevine) not covered in the original AGRIDE-c. Moreover, being a multi-variable damage model, with also some input parameters of uncertain estimation, this study examines the implications of modelling assumptions on damage and risk results to obtain general insights from a modeller's perspective. Finally, the issue of spatial transferability is discussed by comparing model outcomes for cereals in the analysed region and in the Po Plain, for which AGRIDE-c was originally developed. The results highlight the importance, in practical applications, (i) to determine a confidence band for loss estimates that can help for more informed decision making processes and (ii) when transferring models, to verify the similarity between the physical and economic contexts of implementation (and, if necessary, adjust model's input and/or assumptions), in order to prevent inaccurate or distorted damage and risk estimations.

A key issue in the design of side weirs is the experimental assessment of the discharge coefficient. This can be determined by laboratory measurements of discharge and water depths at the up- and downstream ends of the weir by using De Marchi&rsquo, s approach, consisting in the solution of the 1D dynamic equation of spatially varied steady flow with non-uniform discharge, under the assumption of energy conservation. This study originates from a recent alarming proliferation of works that evaluate the discharge coefficient for side weirs without clearly explaining the experimental methodology and/or even incorrectly applying modelling approaches, thus generating possible misinterpretations of the results. In this context, the present paper aims to highlight the effects of using oversimplified and/or heterogenous models (relying on different assumptions) for the experimental determination of the discharge coefficient for side weirs. Furthermore, a sensitivity analysis is performed to detect the most influencing hydraulic and geometric parameters on each considered model. The overall results clearly indicate the wrongness of using or building not homogeneous discharge coefficient datasets to obtain and/or compare predictive experimental discharge coefficient formulas. We finally show how neural networks could provide a possible solution to these heterogeneity issues.

We resolve a useful formulation of the question how a statistician can coherently incorporate the information in a consulted expert’s probability assessment for an event into a personal posterior probability assertion. Using a framework that recognises the total information available as composed of units available only to each of them along with units available to both, we show: that a sufficient statistic for all the information available to both the expert and the statistician is the product of their odds ratios in favour of the event; that the geometric mean of their two probabilities specifies a contour of pairs of assertions in the unit-square that yield the same posterior probability; that the information-combining function is parameterised by an unknown probability for the event conditioned only on the unspecified information common to both the statistician and the expert; and that an assessable mixing distribution over this unspecified probability allows an integrable mixture distribution to represent a computable posterior probability. The exact results allow the identification of the subclass of coherent probabilities that are externally Bayesian operators. This subclass is equivalent to the class of combining functions that honour the principles of uniformity and compromise.

Several studies have demonstrated that in abruptly expanding channels phenomena of flow asymmetry can arise under certain tailwater conditions. These undesired situations are characterized by high-velocity concentrations and backward flows in the tailwater channel. This paper presents some preliminary results of an experimental investigation carried out to study the effects of a system of crossbeams for improving the flow patterns in the tailwater channel. Four different beam spacings, two system orientations and slopes, two locations, and two beam heights were tested in order to define the most adequate geometry of the dissipator. It was found that, for almost all tested configurations, the presence of the crossbeams produced a significant improvement in the flow field in the channel, in terms of velocity distribution and stability under variable downstream conditions.

This paper displays the productive role of the judgment of exchangeability and even conditional exchangeability that should replace the misleading assertion of independence of various experts' opinions regarding uncertain situations. The application is technically rather complicated, and a basic understanding of exchangeability in its simple applications is presumed. One component of the analysis is novel. It suggests how we might specify a likelihood function that allows us to learn about one exchangeable sequence of events from the outcomes of another exchangeable sequence. The substantive content of the the paper concerns the use of personal probabilities by two experts in assessing the sex of human skulls found in anthropological investigations. Although we initially value the two experts' assertions exchangeably, we learn to value one of the expert's assertions more than the other's. Moreover we identify precisely how much to value the elicitation from a second expert after we have already learned the assertion of the first. Valuation is based on a decision theoretic procedure assessing reduction in risk.

In this note we give an altemativity to von Neumann Morgenstem Theory. What we propose is a generalization of a preceeding one (Di Bacco and Regoli, 1994) that assumes the bayesian updating and the additivity of probabilities. We give natural axioms to describe the people’s behaviour in the choice of the “optimal” action and in updating probability assesments. Besides we substitute - in composing probabilities - the additivity with the weaker property of associativity. In these conditions we find again, modulus an isomorphism, Expected Utility Rule and Bayes Rule. More precisely our goal may be summarized in the following three points: 1. Justify the use of the expected utility rule without using the independence axiom which is not universally accepted as “natural” property. 2. Justify the Bayes rule in the context of the statistical theory of decision making, that is in direct connexion with the expected utility rule axiom. 3. Weaken a fundamental characteristic of the probability, the additivit...

Les inferences a propos du comportement, de l'ecologie et de la vie des hominides ont souvent ete realisees par analogie entre les especes vivantes et les especes fossiles. L'A estime que cette methode est erronee pour trois raisons : l'analogie n'est pas realisee a partir d'especes vivantes, les intervales de confidence pour des valeurs predites font plus d'inferences que les usages minimes et sans pratique, la reduction des variations biologiques des especes fossiles a un determinisme des especes fossiles est statistiquement invalide, est une erreur biologique

It is known that the problem of combining a number of expert probability evaluations is frequently solved with additive or multiplicative rules. In this paper we try to show, with the help of a behavioural model, that the additive rule (or linear pooling) derives from the application of Bayesian reasoning. In another occasion we will discuss the multiplicative rule.

In this paper likelihood is characterized as an index which measures how much a model fits a sample. Some properties required to an index of fit are introduced and discussed, while stressing how they describe aspects inner to idea of fit. Finally we prove that, if an index of fit is maximal when the model reaches the distribution of the sample, then such an index is an increasing continuous transform of $$\mathop \Pi \limits_{\iota - 1}^n (p_i )^{qi} $$ , where thep i's are the theoretical relative frequencies provided by the model and theq i's are the actual relative frequencies of the sample.